http://intro2libsys.info/pycon-jp-2015

About

This presentation is about the preliminary results for the development of a Linked Data Fragment Server - built using Python and Redis - for providing a lightweight mechanism for retrieving cached RDF triples for use by Semantic Web applications.

The Problem

Providing a full SPARQL endpoint for both small and large RDF linked-data sets is costly both in time and resources, especially for more complex queries. This often results in poor responses and unreliable service, especially if the SPARQL endpoint trying to handle multiple clients querying the RDF graph database.

A Promising Alternative

Ruben Verborgh of Ghent University in Belgium originated the concept of Linked Data Fragments that offers a middle-ground between different options for accessing RDF graph data. Instead of needing high-powered server to handle the processing load required for hosting a full SPARQL endpoint or the alternative of just providing a data dump where all of the data is processed locally to be useful, the Linked Data Fragments approach instead offers a lightweight querying pattern called a Triple Pattern Fragment that returns one or more triples based on a simplified syntax.


This presentation is licensed under the Creative Commons Attribution 4.0 International License, source code available on Github at https://github.com/jermnelson/pyconjp-2015 and uses Flask and Skeleton.

About RDF & Linked Data BIBFRAME & DPLA Redis Python Falcon & Asynco Experiments Next Steps Resources